DBS-C01 Timed Practice Test 3 — 10 Questions

Question 1

A company runs a data warehouse on Amazon Redshift. The workload has frequent DELETE and UPDATE operations on a large fact table. Over time, query performance degrades. Which maintenance operation should be scheduled regularly to optimize performance?

10 minute time limit — choose an answer to begin.

Accepted Answer

Run VACUUM and ANALYZE commands regularly. B is correct because frequent DELETE and UPDATE operations in Redshift create ghost rows and cause table bloat, degrading query performance. Running VACUUM reclaims space and re-sorts rows, while ANALYZE updates table statistics for the query optimizer; together they restore performance without requiring a full table rebuild.

Answer

Run VACUUM FULL during maintenance windows

Answer

Alter the table to use a different DISTKEY

Answer

Drop and recreate the table periodically

Question 2

Which TWO of the following are benefits of using Amazon RDS Proxy? (Choose TWO.)

Accepted Answer

Reduces the number of database connections by pooling them.. Amazon RDS Proxy acts as a connection broker between your application and the database, maintaining a pool of established connections. When the application opens a new connection, RDS Proxy reuses an idle connection from the pool, which reduces the total number of database connections and prevents the database from being overwhelmed. This pooling mechanism directly addresses the issue of connection exhaustion, especially in serverless or highly concurrent environments.

Answer

Automatically encrypts all traffic between the application and the database.

Answer

Provides built-in read/write splitting for read replicas.

Answer

Reduces storage costs by compressing data in transit.

Question 3

A company is running an Amazon RDS for MySQL Multi-AZ DB instance. The primary instance in us-east-1a experiences an unexpected failure. After the automatic failover, the application team reports that write latency has increased significantly. The new primary instance is in us-east-1b. The DB instance class and storage configuration are identical. What is the MOST likely cause of the increased write latency?

Accepted Answer

The application is connecting to the DB instance in a different Availability Zone, increasing network latency.. After failover, the new primary DB instance resides in us-east-1b, while the application likely continues to connect to the original endpoint or is still running in us-east-1a. This cross-AZ network hop introduces additional latency for write operations, as the application must send data over the network between Availability Zones. The DB instance class and storage are identical, so performance differences are not due to hardware changes.

Answer

The DB instance class in us-east-1b is a different size than the original.

Answer

The Multi-AZ configuration uses asynchronous replication, causing higher latency.

Answer

The new primary is in the same Availability Zone as the application, but the standby is in a different AZ, causing synchronous replication overhead.

Question 4

A company's Amazon Aurora MySQL DB cluster is experiencing a failover event. Which THREE metrics in CloudWatch should be examined to understand the cause of the failover?

Accepted Answer

ACUUtilization. (ACUUtilization) is correct because high ACU utilization can indicate resource exhaustion (CPU/memory pressure) that may trigger a failover in Aurora. Option D (DatabaseConnections) is correct because a sudden spike or drop in connections could signal issues like connection exhaustion or application failures that lead to failover. Option E (FailoverCount) is correct because this metric directly tracks the number of failover events; examining the timestamp of the last increment helps correlate with the incident. Option B (ReadLatency) is wrong because while high read latency can be a symptom, it is not a direct cause of failover; Aurora uses different mechanisms for read scaling. Option C (BinLogDiskUsage) is wrong because it relates to binary log storage for replication, not a direct trigger for failover.

Answer

ReadLatency

Answer

BinLogDiskUsage

Question 5

A company is using Amazon RDS for MySQL with automated backups enabled. The security team requires that all backups be encrypted at rest. Which configuration ensures that new automated backups are encrypted?

Accepted Answer

Create a new encrypted DB instance and migrate the data. Automated backups will inherit encryption.. Encryption at rest must be enabled at creation time on an RDS instance. When you enable encryption at rest on a new DB instance, all automated backups, snapshots, and replicas inherit that encryption automatically. Option B is incorrect because you cannot enable encryption at rest on an existing RDS instance after creation; you must create a new encrypted instance and migrate. Option C is incorrect because automated backups are stored in an S3 bucket managed by RDS, but you cannot directly encrypt the bucket or backups separately; encryption is tied to the DB instance. Option D is incorrect because it incorrectly suggests both enabling encryption on the instance and a separate DBSnapshot option; encryption on the instance already covers backups, and there is no separate DBSnapshot option for enabling encryption.

Answer

Modify the DB instance to enable encryption at rest after creation.

Answer

Use AWS KMS to encrypt the S3 bucket where automated backups are stored.

Answer

Enable encryption at rest on the DB instance and also enable encryption on automated backups using the DBSnapshot option.

Question 6

A media company is migrating a 5 TB MongoDB database to Amazon DocumentDB. The migration must have minimal downtime. The source MongoDB uses sharding across 10 shards. Which migration strategy is MOST appropriate?

Accepted Answer

Use AWS DMS with MongoDB as source and DocumentDB as target, enabling CDC. AWS DMS with CDC (Change Data Capture) is the most appropriate strategy because it supports ongoing replication from a sharded MongoDB source to Amazon DocumentDB, enabling near-zero downtime migration. DMS can handle the 5 TB dataset and 10 shards by using the MongoDB oplog to capture changes after the initial full load, ensuring minimal interruption to the media company's operations.

Answer

Use native MongoDB replication to sync to DocumentDB

Answer

Export data to S3 and use AWS Glue to load into DocumentDB

Answer

Use mongoexport to export data and mongoimport to import into DocumentDB

Question 7

A company uses Amazon Redshift for data warehousing. They run a query that joins a large fact table (10 billion rows) with a small dimension table (1 million rows). The query is slow. The distribution style of the fact table is AUTO, and the dimension table has DISTSTYLE ALL. The join key is user_id. What is the MOST likely reason for the poor performance?

Accepted Answer

The fact table's distribution key is not user_id, causing redistribution. When the fact table uses DISTSTYLE AUTO, Redshift may choose a distribution key that is not user_id. When the fact table is distributed on a different key, joining on user_id requires Redshift to redistribute the fact table rows across nodes to match the dimension table's distribution, causing significant network traffic and slower performance. The dimension table with DISTSTYLE ALL is already replicated to all nodes, so the bottleneck is the fact table's distribution mismatch.

Answer

The dimension table does not have a sort key on user_id

Answer

The dimension table uses DISTSTYLE ALL, which is inefficient for joins

Answer

The fact table should have column compression disabled for the join key

Question 8

A company is building a real-time leaderboard for an online game using Amazon DynamoDB. The leaderboard must update scores within seconds and support queries for top 100 players. Which TWO design patterns should be used? (Choose TWO.)

Accepted Answer

Use DynamoDB Streams to trigger a Lambda function that updates a separate leaderboard table.. DynamoDB Streams can capture score updates in near real-time and trigger a Lambda function to maintain a separate leaderboard table optimized for top-100 queries. This decouples the write-heavy game table from the read-heavy leaderboard, ensuring low-latency updates without contention.

Answer

Create a global secondary index on the score attribute for efficient range queries.

Answer

Store the leaderboard in Amazon ElastiCache for Redis for low-latency reads.

Answer

Set the sort key to the score attribute for natural ordering.

Question 9

Refer to the exhibit. A DBA sees the above log entries for an Amazon Aurora MySQL cluster. What is the most likely cause?

Accepted Answer

There is underlying storage corruption. The logs show page corruption and checksum errors, which are classic symptoms of underlying storage corruption in Aurora MySQL. Storage corruption can occur due to hardware failures or software bugs, and Aurora's distributed storage layer can sometimes experience such issues that manifest as corrupted pages. Option B is incorrect because reader lag would show replication delay metrics and possibly 'seconds behind master' warnings, not corruption-related errors. Option C is incorrect because connection exhaustion would generate errors like 'too many connections' or timeouts, not page corruption. Option D is incorrect because a failed backup restore would typically result in errors during the restore process, not ongoing page corruption after the instance is running.

Answer

The reader instance is lagging behind the writer

Answer

The DB instance has run out of connections

Answer

A recent backup restore operation failed

Question 10

A company is using Amazon RDS for MySQL and has enabled Enhanced Monitoring. The database administrator wants to identify the top contributors to disk I/O. Which THREE metrics from Enhanced Monitoring should they examine?

Accepted Answer

DirtyBufferFlushRate. (DirtyBufferFlushRate) is correct because it indicates the rate at which dirty (modified) buffers are flushed from memory to disk, directly contributing to disk writes and I/O. Option D (WriteOps) is correct as it measures the number of write operations performed on disk, a direct contributor to disk I/O. Option E (PhysicalReads) is correct because it represents read operations that actually hit the disk (i.e., cache misses), contributing to disk I/O. Options B (NetworkThroughput) and C (LogicalReads) are incorrect: NetworkThroughput relates to network traffic, not disk I/O; LogicalReads are reads satisfied from the buffer pool (memory), not disk.

Answer

NetworkThroughput

Answer

LogicalReads